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+/*
+ * Copyright (c) 2017 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#ifdef INTERNAL_ONLY //FIXME Delete this file before the release
+
+#include "arm_compute/runtime/NEON/functions/NEActivationLayer.h"
+#include "arm_compute/runtime/NEON/functions/NEConvolutionLayer.h"
+#include "arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h"
+#include "arm_compute/runtime/NEON/functions/NEPoolingLayer.h"
+#include "arm_compute/runtime/NEON/functions/NESoftmaxLayer.h"
+#include "tests/NEON/Accessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Macros.h"
+#include "tests/networks/LeNet5Network.h"
+#include "tests/validation/Validation.h"
+
+#include <string>
+#include <vector>
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace
+{
+using NELeNet5Model = networks::LeNet5Network<Tensor,
+ Accessor,
+ NEActivationLayer,
+ NEConvolutionLayer,
+ NEFullyConnectedLayer,
+ NEPoolingLayer,
+ NESoftmaxLayer>;
+std::vector<unsigned int> compute_lenet5(unsigned int batches, std::string input_file)
+{
+ std::vector<std::string> weight_files = { "cnn_data/lenet_model/conv1_w.npy",
+ "cnn_data/lenet_model/conv2_w.npy",
+ "cnn_data/lenet_model/ip1_w.npy",
+ "cnn_data/lenet_model/ip2_w.npy"
+ };
+
+ std::vector<std::string> bias_files = { "cnn_data/lenet_model/conv1_b.npy",
+ "cnn_data/lenet_model/conv2_b.npy",
+ "cnn_data/lenet_model/ip1_b.npy",
+ "cnn_data/lenet_model/ip2_b.npy"
+ };
+ NELeNet5Model network{};
+ network.init(batches);
+ network.build();
+ network.allocate();
+ network.fill(weight_files, bias_files);
+ network.feed(std::move(input_file));
+ network.run();
+
+ return network.get_classifications();
+}
+} // namespace
+
+TEST_SUITE(NEON)
+TEST_SUITE(SYSTEM_TESTS)
+
+TEST_CASE(LeNet5, framework::DatasetMode::PRECOMMIT)
+{
+ // Compute alexnet
+ std::vector<unsigned int> classified_labels = compute_lenet5(10, "cnn_data/mnist_data/input10.npy");
+
+ // Expected labels
+ std::vector<unsigned int> expected_labels = { 7, 2, 1, 0, 4, 1, 4, 9, 5, 9 };
+
+ // Validate labels
+ validate(classified_labels, expected_labels);
+}
+
+TEST_SUITE_END()
+TEST_SUITE_END()
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* INTERNAL_ONLY */